Predicting Parkinson’s disease and amyotrophic lateral sclerosis using RNA-Seq-based miRNA profiling in a large prospective cohort

• Applicant: Professorin Dr. Christina Lill
• Subject Area: Human Genetics ; Molecular and Cellular Neurology and Neuropathology
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 459045180

Parkinson’s disease (PD) and amytrophic lateral sclerosis (ALS) are progressively worsening and - in case of ALS - fatal neurodegenerative disorders, with increasing numbers in industrialized, ageing populations. One major goal of translational research is to identify individuals at risk for disease, here PD and ALS, in order to develop strategies to prevent the clinical onset of the disease. However, this requires large prospective cohorts with unaffected individuals at baseline who are followed longitudinally over many years. This is difficult to achieve and, as a result, there is a severe lack of sufficiently sized and appropriately characterized datasets with available pre-disease biomaterials for systematic biomarker identification. MicroRNAs (miRNAs) are a type of non-coding RNAs that fulfill essential functions in the post-transcriptional regulation of gene expression in all tissues, especially in the CNS. Variation in their extracellular composition in blood may reflect the effects of pathophysiological processes, exposure to certain environmental and lifestyle factors, and may be genetically determined. Thus, their investigation as molecular biomarkers for complex disorders including neurodegenerative diseases is highly promising. However, thus far, miRNA biomarker studies in PD or ALS were limited to prevalent disease cases which do not allow inferences on risk prediction due to potential reverse causation.In this project, we propose to make use of one of the largest prospective cohorts ever assembled worldwide (i.e., European Prospective Investigation into Cancer and Nutrition, EPIC) for biomarker identification in pre-disease plasma samples. In EPIC, blood samples were collected at baseline in 521,000 healthy individuals in a highly standardized fashion, then aliquoted and stored in liquid nitrogen. During the more than 20 years of follow-up, a substantial fraction of the participants have been diagnosed with neurodegenerative diseases, including ALS and PD. The main aim of our project will be to assess whether microRNA profiles from blood samples (n=1,300) collected prior to disease onset in EPIC participantes can predict a later conversion to PD and ALS. To this end, we will generate microRNA profiles in pre-disease samples of EPIC individuals who later developed PD (n=500) or ALS (n=300) and will compare them to equivalent profiles of matched controls (n=500) randomly drawn from within the EPIC cohort. In addition, we will generate genome-wide DNA genotyping data and analyze them together with other variables from the extensive EPIC database, including questionnaire-based pre-disease exposure/lifestyle and medical data. In conjunction with another project, recently funded by the Michael-J-Fox Foundation to perform blood-based screenings for novel proteomics biomarkers this project aims to optimize our disease prediction models allowing for an earlier detection, therapy and ultimatively prevention of these devastating diseases.

• DFG Programme: Research Grants